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Research Scientist in Retrieval and Recommendation
NAVER LABS Europe
We’re looking for applications from research scientists, at the junior or senior levels, to join the NAVER LABS Europe Search & Recommendation team. Our main research themes are articulated around the development of novel Interactive Machine Learning techniques for interactive and adaptive Search and Recommendation systems. We’re targeting large-scale on-line applications in a variety of domains such as Conversational Search, News Recommendation and Multimodal/Multilingual Information Retrieval, with a particular attention to causal and counter-factual aspects. We are also working on new user interfaces, mixing voice, gesture, text and image, to enrich the range of human/machine feedback.
Our research is carried out with the ‘NAVER’ search group who run the world’s 5th biggest search engine. This provides research opportunities that go far beyond the traditional Information Retrieval framework and gives us the chance to see millions of users potentially benefiting the outcomes of our research.
We encourage participation in the academic community. Our researchers collaborate closely with universities and regularly publish in venues such as ACL, EMNLP, KDD, SIGIR, ECIR, RecSys, ICML and NeurIPS.
Please refer to the link in this post for more information on requirements and how to apply.
Link: https://europe.naverlabs.com/job/senior-research-scientist-in-retrieval-and-recommendation/
Post-doc in job recommendation
Aalborg University Copenhagen
We have a 3-year post-doc on job recommender systems available at AAU in Copenhagen with an Oct 4 deadline and a Dec 1 starting date. Want to work on high-quality job recommendations for Danish job seekers in collaboration with Jobindex, Scandinavia’s largest recruitment agency and job portal? Check out http://bit.ly/jobmatch-aau and http://bit.ly/jobindex-ad or contact me at toine@hum.aau.dk for more details.
Link: http://bit.ly/jobmatch-aau
Principal Engineer (Search/Personalization) - eCommerce
Grubhub
* Own and oversee large scale technical implementation for Search and Discovery systems to optimize the eCommerce experience
* Pivot between the daily tasks of system design and programming to architecting a strategic vision for how our team can optimize Grubhub’s eCommerce operations
* Collaborate to implement best practices and methodologies with regards to technology choices and changes across the organization
* Contribute to GrubHub’s research roadmap to help identify areas we can improve the business
* Mentor the team to ensure growth of junior peers
Principle product manager
Zalando
As a principal product manager within the recommendations team you will be working on highly visible and high impact customer facing features that directly affect the customer experience of 32 million Zalando customers across app and web. You will drive Zalando’s vision “to become the starting point for Fashion”.

This is a unique opportunity to work in one of the most advanced recommendations teams in Europe and improve how more than 32 million Zalando customers in 17 countries engage with fashion online.

Check out the Job URL for more details or come visit the Zalando booth
Link: https://jobs.zalando.com/en/jobs/2254965-principal-product-manager-recommendation/?gh_src=gk03hq
Applied Scientist-Amazon Search Relevance and Recommendations
Amazon Search
In this role you will be focused on improving the search results for hundreds of millions of Amazon.com customers around the world. Along with your teammates, you will constantly strive to improve search results and relevance ranking across all Amazon categories. You will invent universally applicable signals and algorithms for training machine-learned ranking models and improve the machine-learning framework for training and offline evaluation that is used for all new relevance models.
Link: https://www.amazon.jobs/en/jobs/1262089/applied-scientist
Applied Scientist-Alexa Shopping
Amazon Alexa Shopping
The Alexa Shopping team is looking for Applied Scientists to build the next generation of shopping assistants.
As an applied scientist in Alexa Shopping, you will be responsible for the research, design and development of new natural language, search, and machine learning technologies for voice shopping. You will be working with top scientists and engineers, as well as with product teams and other research partners, both locally and abroad. Your work will combine data mining, systems and software development, exploration of new technologies, as well as publications and presentations at top scientific conferences.
The ideal candidates have deep expertise in one or several of the following fields: Information Retrieval, Web search, Web data mining, Machine Learning, Natural Language Processing, Artificial Intelligence. An ideal candidate shows a bias for action and has a strong understanding of empirical methods. The ability to write clearly and speak convincingly as evidenced through participation in academic conferences and service in the scientific community are a must.
Link: https://www.amazon.jobs/en/jobs/1190659/applied-scientist
Applied Scientist- Amazon Personalization
Amazon Personalization
Want to help invent next generation technologies in recommender systems? Are you looking for roles that impact millions of customers a day, with opportunities to drive billions of dollars in impact? We’ve got the perfect job for you.

Amazon’s Personalization team is looking for an Applied Scientist to work on the core website optimization systems for all of Amazon. You will be part of a multidisciplinary team, working on one of the largest scale machine learning systems in the company. You will hone your skills in areas such as deep learning, multi-armed bandits, and reinforcement learning while building scalable industrial systems. As a member of a highly leveraged team of talented engineers and ML scientists, you will have a unique opportunity to help determine what content gets shown to every customer on Amazon.

As a member of the team, you will use machine learning and analytical techniques to create scalable solutions for business problems. You will propose and run live experiments on customers, with opportunities to publish your work. You bring strong thought leadership, great judgment, clear communication skills, and strong track record of delivery. You will play a critical role in ideation for the team. We are building the next generation optimization system that powers the biggest internet retailer on earth, and we hope you will join us!
Link: https://www.amazon.jobs/en/jobs/1268377/applied-scientist-personalization
Applied Scientist- Amazon Consumer Engagement
Amazon
Do you want to be part of an initiative that is aiming to help change customer shopping behavior on Amazon? The Ask team wants to build engaging customer experiences on Amazon Search and on the Detail Page with a single vision - invest in the right machine learning intelligence to help answer customer questions and provide them the right guidance during their shopping journey. We want customers to begin their shopping exploration on Amazon, not on a search engine. We are looking for an Applied Scientist to research and apply ML solutions to a number of innovative initiatives planned and to help drive the productionizing of these models at Amazon Search and Detail Page scale. As a part of this role, you will be developing solutions for NER, parsing, NLU and own interfacing with the Information Retrieval, NLP/NLU, and HCI research communities to advance the state of the art and the state of Amazon’s business in extracting knowledge and information from diverse types of unstructured, semi-structured, and structured community contributions. You will be an advocate for prioritizing innovative technology-driven and research-driven experiences in our most visible surfaces. The ideal candidate will be an expert in the area of Machine Learning (ML) in general and NLP specifically and will have a strong record of delivering results. We are moving fast to change the way customers shop on Amazon. As an Applied Scientist, you will help tackle a variety of technical challenges and mentor a growing team of engineers and scientists. Together with a multi-disciplinary team of scientists, senior engineers, and senior product managers you will work on building engaging experiences for customers with NLP and ML at its core. Along the way, you’ll learn a ton, have fun and make a positive impact on millions of people.
Link: https://www.amazon.jobs/en/jobs/1260992/applied-scientist
Sr Machine Learning Scientist-Consumer Engagement Tech
Amazon Consumer Engagement
Do you want to join an innovative team of scientists who invent and apply the most advanced machine learning, NLP and machine translation techniques to create the best customer engagement experience on the earth? Do you want to revolutionize the way how customers solve their issues and got their questions answered? Do you want to help enabling any Amazon associates to aid any Amazon customers no matter what language they speak? At Customer Engagement Technology, we develop peculiar products that help customers solve problems. Our team leads the technical innovations in these spaces and set the bar for every other company that exists. We love data, and we have more than anyone else in the industry. We innovate on behalf of customers, developing Bot, self-service, and associate-facing products that delight customers and support our world class customer service workforce. We leverage big data, NLP, ML, and a focus on continuous innovation to create an amazing experience for customers as we scale to meet business growth each year.
If you like to own solving end-to-end business problems with machine learning which would have a direct impact on the bottom line of Amazon’s business while improving customer experience, if you see how big data and cutting-edge technology can be used to improve customer experience, if you love to innovate, to discover knowledge from big structured and unstructured data and if you deliver results, then we want you to be in our team.
Link: https://www.amazon.jobs/en/jobs/1199459/sr-machine-learning-scientist
Applied Scientist- Amazon Community Shopping Team
Amazon Social Shopping
Customer Reviews, Deals and Content Moderation are community driven experiences that are key to the Amazon experience worldwide. Join the applied research team in Berlin, Germany supporting Community Shopping and driving the customer experience for these important programs.

The problems are real, with tangible customer impact. The work sits at the intersection of research and engineering, driving better quality in our reviews corpus, ensuring appropriate content across customer-submitted text, images and video at massive scale, and ensuring that the right deals surface for the right customer at the right time. The applications are wide and range from Generic ML to NLP and Computer Vision.

We are an applied research group in Berlin, Germany creating novel solutions in collaboration with product and engineering teams at the core of some of Amazon’s biggest and most engaged systems. If that sounds interesting for you and if you would like to live in one of the most exciting places of the world, then we have the perfect role for you. We have open Applied Scientist positions for all levels of experience and this is what we are looking for.
Link: https://www.amazon.jobs/en/jobs/1047516/applied-scientist
Applied Scientist- Amazon Customer Behavior Analytics
Amazon Consumer Engagement
The Customer Behavior Analytics (CBA) Org builds products from the ground up to serve internal teams. Products we developed include Downstream Impact (DSI) framework, Customer Targeting applications, and A/B testing platforms. We use cutting edge technologies that fuse Big Data with concepts from Machine Learning, Economics, and Data Science. These innovations help make strategic investment decisions and define the customer engagement metrics by which Amazon runs its business globally.

The High Value Message (HVM) Analytics team within CBA is looking for an Applied Scientist to make an impact on how Amazon influences our shopper's perception. You will work with distributed machine learning and statistical algorithms across multiple platforms to harness enormous volumes of online data at scale to match customers and products/offers based on probabilistic reasoning. Our primary partners are Cross Channel Marketing and Digital Corporate Advertising team. A successful Applied Scientist has an entrepreneurial spirit and want to make a big impact on Amazon and our shoppers. You are excited about cutting-edge research on Deep Learning, Natural Language Processing (NLP), causal inference, and experimental design. You enjoy building massive scale and high-performance systems but also have a bias for delivering simple solutions to complex problems. We are looking for a thought leader and you demonstrate this by deploying solutions into production, not just by having ideas. We encourage you to challenge yourself and others to come up with better solutions. You will develop strong working relationships and thrive in a collaborative team environment. You need to be fluid in:
AWS services (e.g. EMR, s3).
Feature extraction, feature engineering and feature selection.
Machine learning, statistical algorithms and recommenders.
Model evaluation, validation and deployment.
Casual Inference.
Experimental design and testing.
Link: https://www.amazon.jobs/en/jobs/1193348/applied-scientist-ii
Applied Scientist- Digital Content
Amazon Digital Content Team
How can we improve the customer experience by tailoring the information we have to provide a seamless shopping experience? How do we build different models leveraging algorithms that will help us innovate? What is the relationship between what the customer actually thinks vs. what is being suggested vs what they actually end up buying? How can we do all of this without disrupting the customer experience and also understand the customer without asking them? Does that sound fun and interesting? The solution or answers to these questions and others like them are fundamental in helping Digital Content businesses.

Digital Content is a growing multi-disciplinary team addressing everyday customer needs through a combination of software engineering, web development, hardware development, and applied research. Today the online shopper's largest friction is evaluating fit and size, and other details. Our team’s ultimate goal is for customers to easily discover items they will like and to get the right one the first time they look for it.

As an applied scientist, you will be using Amazon’s large-scale computing resources to build models describing best suited recommendations and work with domain experts and engineers to turn those models into production solutions. You will participate in the Amazon ML community and mentor Applied Scientists and software development engineers with a strong interest in and knowledge of ML. Your work will directly benefit customers and the Digital Content business, such as Kindle, Amazon Music, Audible and much more. We are looking for passionate, hard-working, and talented Applied scientist who have experience building mission critical, high volume applications that customers love. You will have an enormous opportunity to make a large impact on the design, architecture, and implementation of cutting edge products used every day, by people you know.
Link: https://www.amazon.jobs/en/jobs/937593/senior-applied-scientist
Applied Scientist- Alexa Shopping
Amazon Alexa Shopping NLP
You: Alexa, I am looking for a new career opportunity, where I could do innovative development in AI and impact millions of customers, what do you suggest?
Alexa: The Alexa Shopping team is looking for Research Engineers to help me become the best personal shopping assistant. Do you want to hear more?
You: Yes, please!
The Alexa Shopping team is looking for Applied Scientists to build the next generation of shopping assistants.
As an applied scientist in Alexa Shopping, you will be responsible for the research, design and development of new natural language, search, and machine learning technologies for voice shopping. You will be working with top scientists and engineers, as well as with product teams and other research partners, both locally and abroad. Your work will combine data mining, systems and software development, exploration of new technologies, as well as publications and presentations at top scientific conferences.
The ideal candidates have deep expertise in one or several of the following fields: Information Retrieval, Web search, Web data mining, Machine Learning, Natural Language Processing, Artificial Intelligence. An ideal candidate shows a bias for action and has a strong understanding of empirical methods. The ability to write clearly and speak convincingly as evidenced through participation in academic conferences and service in the scientific community are a must.
Link: https://www.amazon.jobs/en/jobs/1233997/applied-scientist-alexa-shopping
Assistant professor explainable AI
University of Maastricht
Tenure track position in explainable AI. Track record with multidisciplinary collaboration (e.g. FAccT conference) preferred.
Link: None
Postdoc explainable AI
Maastricht University.
2 yr Postdoc in XAI. Preferably with background in NLP or NLG.
Link: None
Data Scientist - SmartMatch (Job RecSys)
Randstad Group Netherlands
As one of the biggest recruitment organisations in the world, Randstad Groep Nederland is constantly improving its business and processes. Data, AI, and you as one of our Data Scientists, are therefore indispensable! 

Randstad, Yacht and Tempo-Team have access to vast amounts of data between them. Over two billion records: the attributes of millions of candidates, and data belonging to clients, potential candidates and our own organisation. A treasure trove of information that our Data Scientists continuously explore to improve our business! 
 
As part of our smartmatch team, you specifically help us develop and implement solutions that make us smarter and faster. You work on our production-scale recommender system, based in NLP, that support our recruiters and clients in making the best matches between candidate and company. This means you will also try to answer questions like ‘how do we avoid creating the same biases in our AI solutions that us humans can hold?’ and ‘how do we use data in a way that is fair?’.
 
We expect you to contribute in all phases of the development cycle of complex machine learning models, from idea incubation, experimentation, to prototyping and industrialization. 
Link: https://www.werkenbijrandstad.nl/nl/nl/job/R-16854/Data-Scientist
Senior Research Scientist - Algorithms Engineering
Netflix
Want to research and develop improvements to the core algorithms such as recommendations and search that power the Netflix experience that over 193+ million members worldwide see each time they log in? Our Algorithms Engineering team is looking for passionate and talented applied machine learning experts to lead the way by researching and developing the next generation of algorithms used to drive the Netflix experience. This spans central areas of our product including how we approach recommendation systems (e.g. ranking, page generation), personalization (e.g. evidence, search, messaging, marketing), media assets generation and optimizing Netflix-wide systems & infrastructure.

In this role, you will conduct applied research by conceptualizing, designing, implementing, and validating potential algorithmic improvements. This includes running offline experiments and building online A/B tests to run in production systems. To be successful in this role, you need a strong machine learning background, solid software development skills, a love of learning, and to collaborate well in multi-disciplinary teams. You will need to exhibit strong communication and leadership skills, an ability to set priorities, and an execution focus in a dynamic environment.

If you are ready to make a difference at a company that matters, and if you want to work on machine learning and data in a company that strongly believes in both, then we would love to talk to you.

To learn more about our research work, you can visit our research page here: https://research.netflix.com
Link: https://jobs.netflix.com/jobs/860513
Machine Learning Scientist
Layer 6
In this role you will research, develop, and apply new techniques in the intersection of deep learning and personalization. We’re looking for someone with a PhD in Computer Science, Statistics, Operations Research, Mathematics or a related field. See our publications https://layer6.ai/publications/.
Link: https://layer6.ai/careers/
Machine Learning Engineer
Layer 6
We are looking for world-class engineers to tackle cutting-edge problems of applying Machine Learning in the real world. Join this team to help develop a system that will serve as the main interface to our machine learning platform. The goal of this system is to help in all stages of model development, from feature engineering all the way to production monitoring.
Link: https://layer6.ai/careers/
Senior Software Engineer, Recommendations
Flipboard
Do you want to use your software engineering expertise to re-imagine how users can find the best, most relevant content to read?
Flipboard is a content discovery platform for your passions, interests, and news. Available on web, iOS, and Android, Flipboard offers the world important and influential articles shared by the greatest publishers and our awesome Flipboard community to advance conversation, keep people informed, and inspire them to engage, learn, and lead.
At Flipboard we are re-imagining how people consume news and information in the world. The Recommendations team deals with billions of daily signals to help users in the face of information overload by:
– Producing feeds tailored to users’ interests while adhering to sound journalistic principles
– Connecting users and recommending articles, videos, topics, magazines and commerce
– Using a wide range of data-driven techniques drawn from machine learning, collaborative filtering, natural language processing, psychology and old-fashioned straight-up product design
The team is based in Vancouver, Canada and fully remote during the pandemic. We have a flexible work from home policy and are open to hiring remote engineers close to Pacific Timezone, preferably in Canada.
Responsibilities:
– Work with an interdisciplinary group of engineers, data scientists, designers and editorial staff to scale and develop our content recommendation products
– Own the full model lifecycle: from research and implementation to production and refinement
– Participate in data collection, analysis, distributed architecture, algorithm development, product design and mentorship
– Run experiments to draw insights and inform further worthwhile pursuits. The systems you build will scale to millions of daily active users
– Have substantial independence and responsibility from Day One
Link: https://about.flipboard.com/job/senior-software-engineer-recommendations/
Senior Machine Learning Engineer
Pandora/SXM
As part of the Shared Science Foundation team, you will design and build systems that solve prevalent science problems across SiriusXM and Pandora’s digital products. These extensible, shared systems power personalization, content understanding, and advertising and marketing science. You will collaborate with scientists, engineers, and product managers to develop tools, platforms, and infrastructure that accelerates innovation of the entire organization. Your hybrid skill set of machine learning, software engineering, and empathetic communication uniquely positions you to architect systems with multiple stakeholders.
Link: https://jobs.jobvite.com/siriusxm/job/obH3cfwR
Postdoc researcher in explainable machine learning and survival analysis Postdoc researcher in explainable machine learning and survival analysis
KU Leuven
Responsibilities

The candidate will interact with researchers active in health and education. In the health domain, we are primarily focusing on clinical decision support systems. These tools often involve risk prediction models for medical conditions, where both accuracy and interpretability are of high importance. In the domain of education and training, we focus on decision support for learners and teachers/experts, and develop novel techniques for recommending learning tasks matched to the skills and interests of learners, for automated assessment of learning tasks that involve multiple skills (e.g. essays), and for predicting dropout in learning environments that require high self-regulation (e.g. MOOCs). In this domain, the candidate interacts with researchers in imec’s Smart Education research programme, both within itec and with research groups at the universities of Ghent (UGent) and Brussels (VUB), as well as with imec. One research direction that is important in both application domains is time-to-event prediction (survival analysis), which is on the border between statistics and machine learning, and will be of great importance for this function.
Link: https://www.kuleuven.be/personeel/jobsite/jobs/55881116?hl=en&lang=en
Data Scientist
Silver Egg Technology
Work with Japan's leading recommendation-as-a-service provider.
Link: http://silveregg.co.jp
CTO
Silver Egg Technology
Work with Japan's leading recommendation-as-a-service provider.
Link: http://silveregg.co.jp
Lead Data Scientist, Recommendations
Katch Media
Katch Media is seeking a data scientist to lead the development of our next-generation recommendation engine. Individuals in this role are expected to be recognized experts in identified research areas such as artificial intelligence, machine learning, advanced statistics, computational neuroscience, and applied mathematics, particularly areas such as deep learning, graph models, personality modeling, reinforcement learning, natural language processing and data representation. The ideal candidate will have a keen interest in producing new science around the way recommendation systems work. Required skills include hands-on experience with libraries and tools like Spacy, NLTK, Stanford core NLP, Genism, word2vec, johnsnowlabs. Also familiarity with NLP/ML tools and packages like Caffe, PyTorch, TensorFlow, Weka, scikit-learn, NLTK, BERT, GPT-2/GPT-3, etc.
Link: http://www.katch-media.com
Sr. Applied Scientist- Amazon Music
Amazon Music
Can Alexa help anyone experience the music they enjoy? Even if they don't know what they'd like to listen to in this moment? Or, if they know they want “Happy rock from the 90s”, can she help them find it?

Your machine learning skills can help make that a reality on the Amazon Music team. We are seeking an Applied Scientist who will join a team of experts in the field of machine learning, and work together to break new ground in the world of understanding and classifying different forms of music, and creating interactive experiences to help users find the music they are in the mood for. We work on machine learning problems for music classification, recommender systems, dialogue systems, NLP, and music information retrieval.

You'll work in a collaborative environment where you can pursue ambitious, long-term research, with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the experience of Amazon Music customers on Alexa/Echo, mobile, and web.

The successful candidate will have a PhD in Computer Science with a strong focus on machine learning, or a related field, and 2+ years of practical experience applying ML to solve complex problems in recommender systems, information retrieval, signal processing, NLP or dialogue systems. Great if you have a passion for music, but this is not a requirement.
Link: https://www.amazon.jobs/en/jobs/1279742/sr-applied-scientist-amazon-music
Sr. Applied Scientist-Personalization
Amazon-Personalization
Take Earth's most customer-centric company. Mix in hundreds of millions of shoppers spending tens of billions of dollars annually, an exciting opportunity to build next-generation shopping experiences, Amazon’s tremendous computational resources, and our extensive e-Commerce experience. What do you get? The most exciting Recommendations/Personalization position in the industry.

Are you passionate about working on disruptive ideas? Are you obsessed with finding and building the most innovative and customer-friendly user experiences? Have you built and launched new experiences that impact shoppers all around the world? This is a unique opportunity that combines the ability to build exciting, new user experiences for Amazon's customers, with the opportunity to work with Big Data, Machine Learning, and other advanced techniques to provide the best personalized experience for hundreds of millions of Amazon's customers.

As a Senior Applied Scientist, you will be responsible for designing, developing, and deploying large-scale data mining solutions and distributed machine learning systems that ultimately make shopping on Amazon delightful and functional. You will collaborate closely with teams of software engineers, applied machine learning scientists, product managers, user interface designers, and others in order to influence our business and technical strategy, and play a key role in defining the team’s roadmap.
Link: https://www.amazon.jobs/en/jobs/1251020/senior-applied-scientist-personalization
Software Development Manager - Big Data, ML, Search, Knowledge Graphs
Amazon-Personalization
As the software manager on the product knowledge team, based in Seattle, you will play a key role in the establishment of a new platform, with opportunities to create enormous benefit for our customers and Amazon. You will manage the team that takes academic research from theory to production implementation by overcoming performance, scalability, and resiliency challenges. You should enjoy optimization through rapid experimentation, have extremely high standards, and strong ability to implement in the face of ambiguity. Expertise in specialized areas such as Machine Learning, Natural Language Processing, Text Mining, Graph Processing, Search, Recommendation Systems, or Signal Processing, is desired.

You will be recruiting software development engineers. We seek a creative lead who: (1) is passionate about their work, (2) works well with others, (3) has a positive attitude, and (4) can collaborate closely with the product graph science team and other client teams.

You will lead a talented and nimble team of engineers to design and build several services. Responsibilities include direct management of engineers, processes ensuring quality of software development and releases, strategic planning, project management for software within the team.

You will work closely with the Science Lead and the science team to bring new ML and graph-based algorithms into production.

You will work closely with the product manager to help define the product features, roadmaps, and use cases to deliver services to current and future client teams.
Link: https://www.amazon.jobs/en/jobs/1079910/software-development-manager-big-data-ml-search-knowledge-graphs
Applied Scientist - Fashion Recommendations
Zalando
The Fashion Recommendations Team is at the core of Zalando’s browsing experience and fashion discoverability. Our purpose is to play a key role in making Zalando the starting point of fashion by providing recommendations that meet our customers’ fashion needs and wishes while understanding their unique style, preferences and interests.

In this role, you will: design ML solutions that serve our customers’ needs; build data pipelines and models using, for example, AWS, Python and TensorFlow; define hypotheses and A/B test them to validate your use case; and deploy solutions into production to serve more than 33 millions of customers

You will be part of a talented cross-functional team made up of Applied Scientists, Data Engineers and Backend Engineers. You will also count with the support of Product Managers and Designers to create the customer experience that you will deliver.
Link: https://jobs.zalando.com/en/jobs/2301504-applied-scientist-fashion-recommendations/
Senior Applied Scientist - Fashion Recommendations
Zalando
The Fashion Recommendations Team is at the core of Zalando’s browsing experience and fashion discoverability. Our purpose is to play a key role in making Zalando the starting point of fashion by providing recommendations that meet our customers’ fashion needs and wishes while understanding their unique style, preferences and interests.

As a senior member of the team, you will: translate new use cases into a sequence of actionable milestones for your team, drive the design of ML solutions that serve our customers’ needs; build data pipelines and models using, for example, AWS, Python and TensorFlow; define the team’s experimentation roadmap to validate your use cases; and deploy solutions into production to serve more than 33 millions of customers

You will be part of a talented cross-functional team made up of Applied Scientists, Data Engineers and Backend Engineers. You will also count with the support of Product Managers and Designers to create the customer experience that you will deliver.
Link: https://jobs.zalando.com/en/jobs/2348003-senior-applied-scientist-fashion-recommendations/
Sr. Data Scientist and Data Scientist
Home Depot
Data scientists who are specialized in e-commerce recommender systems.
Link: None
Internship, Advertising & Marketing Science (Fall 2020)
Pandora/SXM
You will join a team of scientists with diverse expertise in machine learning, statistics, predictive modeling and economics, and apply cutting edge methodologies to build the next innovations that will delight millions of listeners.
Link: https://jobs.jobvite.com/siriusxm/job/oXPmdfw5
Internship, Content Science (Fall 2020)
Pandora/SXM
The content science team builds data science products and services for content creators such as artists, podcast and talk show hosts, curators, and programmers. We create the best-in-class curated audio catalog and programs, promote audio content, programs, and live events, and build personalized listening experiences for talk shows and podcasts.
Link: https://jobs.jobvite.com/siriusxm/job/oEWndfwU
Internship, Shared Science Foundation (Fall 2020)
Pandora/SXM
In this role you'll be working on a team designing and building the next innovations that will delight millions of listeners. You will have access to billions of hours of music listening history across hundreds of millions of listeners who have provided a hundred billion thumbs on their stations and playlists. And truly unique to SiriusXM + Pandora, you'll be working with extremely rich and diverse interlinked music and talk metadata, including annotations of our expert musicologists with the Music Genome Project's 450+ musical characteristics. With these resources at your fingertips, you will build systems that accelerate innovations in personalization, content understanding, and advertising and marketing science.
Link: https://jobs.jobvite.com/siriusxm/job/oKQmdfwT
Data Scientist, Online
The Home Depot
This role will be responsible for building large-scale systems that analyze terabytes of data. By partnering with business leaders and leveraging company and industry data, this position will also develop algorithms and models to improve business objectives, in areas of online retail and marketing. The Sr. Data Scientist will be expected to operate with minimal supervision and mentor data scientists to complete analytical tasks and productionalize model-driven solutions.
Link: https://careers.peopleclick.com/careerscp/client_homedepot/external/gateway.do?functionName=viewFromLink&jobPostId=356565&localeCode=en-us
Senior Principal Scientist - Artificial Intelligence
Zalando
In this role, you will report directly to the SVP, Builder Platform and Artificial Intelligence (AI). You will be responsible for the scientific bar across the whole company and be expected to have an in-depth understanding of all business-relevant algorithms used across business-critical Zalando systems. This role operates across organizational boundaries and optimizes for the Zalando Group as a whole. It is a role that influences by demonstrating depth, delivering research results and building of prototypes, not through project or process management.

You will be the go-to person for all scientists and senior technical leaders at Zalando because of your deep and broad scientific expertise, and develop and operate mechanisms that establish and maintain a high standard of scientific documentation and reviewing of algorithmic solutions.

You will have one in-depth area where you are expected to work on a solution that not only unifies existing algorithm solutions but also advances the state-of-the-art. This area will be reviewed every six months between you and the SVP, Builder Platform and AI, based on strategic priorities, current needs (e.g., surfaced through senior technical leaders) and scientific advances. Such areas include forecasting, pricing, computer vision, natural language processing, real-time learning, search or algorithmic fairness & privacy.

In essence, you will spend some of your time on consulting and mentoring other scientists, but the majority of your time will be spent on advancing state-of-the-art research in a strategically important area.

You are not a people manager, but you will be expected to be influential across Zalando by constantly demonstrating scientific depth (in one area) and breadth (across all areas). You will use scalable mechanisms to lead others and coordinate closely with the Principal Engineering community leaders at Zalando to ensure that scientific solutions end up in scalable software solutions.
Link: https://jobs.zalando.com/en/jobs/2196437-senior-principal-scientist-artificial-intelligence-w-m-d/
Applied Scientist Full Text Search (NLP)
Zalando
As an applied scientist in Zalando’s search team you will work in a cross-functional team applying the latest developments in machine learning / artificial intelligence to deliver relevant search results to our 34 million monthly active users.

Your main challenges will include working with large amounts of data, delivering high-quality search results using a combination of IR and AI methods. This could involve working on neural models to retrieve the most relevant search results to our customers, or creating user behavioural models to better understand the intent of a customers search query.

WHERE YOUR EXPERTISE IS NEEDED

Keep up to date with the state of the art in information retrieval, natural language processing and deep learning.
Build our query understanding and retrieval machine learning models and pipelines to create fantastic customer experiences.
Solve fashion industry search challenges where personal taste, a trendy vocabulary or challenges such as fit do matter.
Make a positive impact on our scientific culture, encouraging knowledge sharing, and driving technical discussions within the team.
Dig your nose deep into the latest search developments. Challenge the status quo by being eager to discuss your thoughts with the professional community.
Link: https://jobs.zalando.com/en/jobs/2332284-applied-scientist-nlp-full-text-search-w-m-d/
Software Engineer Recommendation Systems
Zalando
Fashion Recommendations program leverages machine learning in their recommendation algorithms which has a large impact on our customers by providing a tailored and relevant shopping experience. As a Software Engineer, you will work with large amounts of data, providing a rock solid, low-latency, large scale production system. You’ll work mostly with Java (Spring Boot), AWS, Kubernetes



WHERE YOUR EXPERTISE IS NEEDED

Design, build and improve large-scale software solutions for customer-facing products with high-throughput on AWS/Kubernetes

Scale our infrastructure to future needs by enabling fast and efficient machine learning algorithmic development and production

Further enriching our engineering culture by encouraging knowledge sharing and driving technical discussions within the team

End to end responsibility of projects, interact with various teams and stakeholders with an entrepreneurial mindset and drive the whole development cycle

Link: https://jobs.zalando.com/en/jobs/2282511-software-engineer-recommendation-systems/
Search Engineer
Zalando
As a relevance engineer in Zalando’s search team you will index and search 500k articles, with 4k article updates and 12k requests per second for 17 markets in 16 languages. You will drive relevancy in a complex industry where personal taste, trends and fit do matter.

Your main challenges will include working with large amounts of data, delivering high-quality search results using a combination of IR and AI methods as well as the operation of one of the biggest european based Elasticsearch clusters on top of Kubernetes. The job will give you the chance to learn from experienced Search and Research Engineers in the industry.


WHERE YOUR EXPERTISE IS NEEDED

Build our query understanding and indexing pipelines powered by the latest developments in information retrieval and AI.

Solve fashion industry search challenges where personal taste, a trendy vocabulary or challenges such as fit do matter.

Make a positive impact on our engineering culture, encouraging knowledge sharing, and driving technical discussions within the team.
Dig your nose deep into the latest search developments.

Challenge the status quo by being eager to discuss your thoughts with the professional community.
Link: https://jobs.zalando.com/en/jobs/2270260-search-engineer/
Recommender Systems Researcher
Comcast
The Comcast Applied AI team is looking for a machine learning expert to join our personalization team. In this role, you will be developing and working on machine learning models for recommendation, personalization, and ranking. You will be responsible for solving challenging problems such as: how to balance exploration and exploitation in recommendation systems? How to address fairness and bias in recommendation systems? How to use different modalities of data to improve the recommendation models? How can reinforcement learning be leveraged in recommendation systems to optimize long-term engagement metrics?
Link: https://career8.successfactors.com/sfcareer/jobreqcareer?jobId=219883&company=21114P
Machine Learning Engineer - Search and Recommendations
Twitter
Who We Are: Twitter is serving the public conversation, and conversations are happening on Twitter every day about every subject and any event. The Search and Recommendations team's job is to connect our users to the conversations and people that are relevant to them.

Search and Recommendations builds infrastructure and models to support this mission across multiple product areas. We are responsible for the recommendations you see under Search, Explore, Trends, Topics, the Home Timeline. The unrivaled challenges that we face at Twitter are both the data scale and the real-time nature of the product. How do you find the most meaningful content among hundreds of millions of new tweets for hundreds of millions of users every day at Twitter? We build large scale personalized recommendation engines utilizing different kinds of signals such as social network, user activity, and geolocation. We work on machine learning, trend detection, search understanding and retrieval, graph algorithms, recommendation systems, distributed systems, and social graph analysis.
Link: https://smrtr.io/4qskd
Engineering Manager - Search and Recommendations
Twitter
Who We Are: Twitter is serving the public conversation, and conversations are happening on Twitter every day about every subject and any event. The Search and Recommendations teams job is to connect our users to the conversations and people that are relevant to them.

Search and Recommendations builds infrastructure and models to support this mission across multiple product areas. We are responsible for the recommendations you see under Search, Explore, Trends, Topics, as well as a portion of your Home Timeline. The unrivaled challenges that we face at Twitter are both the data scale and the real-time nature of the product. How do you find the most meaningful content among hundreds of millions of new tweets for hundreds of millions of users every day at Twitter? We build large scale personalized recommendation engines utilizing different kinds of signals such as social network, user activity, and geolocation. Most of our work is about trend detection, search understanding and retrieval, graph algorithms, recommendation systems, distributed systems, and social graph analysis.

Qualifications
What You'll Do: We are looking for Engineering managers that can provide leadership to their teams and guide them in achieving this mission of connecting users with content most relevant to them on Twitter. You will lead diverse, capable, and driven Systems and ML Engineers and align their career ambitions with business requirements and opportunities. You will collaborate broadly to develop products and technologies to achieve the mission.
Link: https://smrtr.io/4qskM
Staff Machine Learning Engineer
Spotify
What you’ll learn and do:

Improve the quality of Spotify’s personalized listening recommendations in playlists for our huge number of listeners, across many countries
Define and implement standard methodologies for building and evaluating machine learning models for playlists
Define the requirements for measuring and monitoring online ML model performance
Provide technical leadership to machine learning engineers
Collaborate with a multi-functional, agile team, spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and relevant ways
Drive optimization, testing, and tooling to improve quality
Be an active contributor to the Spotify group of machine learning practitioners
Link: https://www.spotifyjobs.com/job/staff-machine-learning-engineer-personalization/
Big Data Engineer
Sovendus
We are looking for a (Big) Data Engineer for our Data Department. Join us and help shaping our Recommender Systems ...among other things!
The job description is in German, but we speak English :)
Link: https://www.sovendus.com/de/karriere/offene_jobs/?jh=4c2o7uhnyyx5wbe5d0474w8x6bjdhe9
Senior Machine Learning Engineer
Tubi
Responsibilities:
Design and develop state of the art machine learning models for various supervised and unsupervised machine learning tasks to improve recommendations, targeting and search.
Own end-to-end productionization of the machine learning algorithms including prototyping new ideas and writing code for A/B tests and production.
Conduct AB tests to prove your ideas and share your learnings from the experiment results.
Develop both machine learning and business specific metrics
Your background:
3+ years in a Machine Learning/Advanced Analytics environment pushing production-level code
BS, MSc or PhD in Computer Science, Operations Research, Statistics, Applied Mathematics, Physics or related field
Industry experience in a data related role
Hands on experience or large scale academic projects on recommender systems, reinforcement learning, contextual bandits, deep learning, non-linear optimization, learning to rank, etc.
Experience writing production-quality code in Python and/or Scala
Previous experience with Apache Spark or other distributed computing frameworks
Link: https://tubi.greenhouse.io/plans/1428660
Senior Data Engineer
Tubi
About the role:

At Tubi, you will work closely with a stellar team of engineers with a passion for learning through solving the most challenging problems using cutting-edge technology. In this Data Engineering role, you will be building real-time systems to handle data at massive scale, created by millions of viewers all over the world enjoying the largest content library in streaming. You will enable machine learning engineers to iterate and experiment faster than ever before. You will help data scientists take ideas to production in days or weeks, not months or years. And you will build tools to enable data analysis and modeling for even the least tech-savvy colleagues. In short, you will enable Tubi to be truly data-driven.

Responsibilities include:

Creating high quality, scalable, streaming data pipelines connecting us to all of our users. Improving ML workflows and designing the next-generation data platform for automating ML. Building low latency and low maintenance ETL infrastructure that powers the whole company.


Your background:

4+ years of a proven track record in a data engineering or related role.
Strong knowledge with Spark DataFrame/DataSet, Spark SQL, Streaming process and cloud storage (e.g., S3).
Ability to take ownership of scalable data pipelines.
A passion for shipping production-quality code.
Scala is not required but preferred.
Prior experience with Kafka, Kinesis, or equivalent is also a plus.
Benefits:

A tight-knit team of passionate people and a tech-first business
Autonomy and end-to-end ownership
We're a well-funded company with stellar revenue growth
We offer very competitive pay, full medical, dental & vision benefits, catered lunch and dinner, etc
Opportunity for internal growth
Link: https://boards.greenhouse.io/tubitv/jobs/2338145
Senior Data Engineer
Tubi
About the role:

At Tubi, you will work closely with a stellar team of engineers with a passion for learning through solving the most challenging problems using cutting-edge technology. In this Data Engineering role, you will be building real-time systems to handle data at massive scale, created by millions of viewers all over the world enjoying the largest content library in streaming. You will enable machine learning engineers to iterate and experiment faster than ever before. You will help data scientists take ideas to production in days or weeks, not months or years. And you will build tools to enable data analysis and modeling for even the least tech-savvy colleagues. In short, you will enable Tubi to be truly data-driven.

Responsibilities include:

Creating high quality, scalable, streaming data pipelines connecting us to all of our users. Improving ML workflows and designing the next-generation data platform for automating ML. Building low latency and low maintenance ETL infrastructure that powers the whole company.


Your background:

4+ years of a proven track record in a data engineering or related role.
Strong knowledge with Spark DataFrame/DataSet, Spark SQL, Streaming process and cloud storage (e.g., S3).
Ability to take ownership of scalable data pipelines.
A passion for shipping production-quality code.
Scala is not required but preferred.
Prior experience with Kafka, Kinesis, or equivalent is also a plus.
Benefits:

A tight-knit team of passionate people and a tech-first business
Autonomy and end-to-end ownership
We're a well-funded company with stellar revenue growth
We offer very competitive pay, full medical, dental & vision benefits, catered lunch and dinner, etc
Opportunity for internal growth
Link: https://boards.greenhouse.io/tubitv/jobs/2338145
Senior Data Engineer
Tubi
About the role:

At Tubi, you will work closely with a stellar team of engineers with a passion for learning through solving the most challenging problems using cutting-edge technology. In this Data Engineering role, you will be building real-time systems to handle data at massive scale, created by millions of viewers all over the world enjoying the largest content library in streaming. You will enable machine learning engineers to iterate and experiment faster than ever before. You will help data scientists take ideas to production in days or weeks, not months or years. And you will build tools to enable data analysis and modeling for even the least tech-savvy colleagues. In short, you will enable Tubi to be truly data-driven.

Responsibilities include:

Creating high quality, scalable, streaming data pipelines connecting us to all of our users. Improving ML workflows and designing the next-generation data platform for automating ML. Building low latency and low maintenance ETL infrastructure that powers the whole company.


Your background:

4+ years of a proven track record in a data engineering or related role.
Strong knowledge with Spark DataFrame/DataSet, Spark SQL, Streaming process and cloud storage (e.g., S3).
Ability to take ownership of scalable data pipelines.
A passion for shipping production-quality code.
Scala is not required but preferred.
Prior experience with Kafka, Kinesis, or equivalent is also a plus.
Benefits:

A tight-knit team of passionate people and a tech-first business
Autonomy and end-to-end ownership
We're a well-funded company with stellar revenue growth
We offer very competitive pay, full medical, dental & vision benefits, catered lunch and dinner, etc
Opportunity for internal growth
Link: https://boards.greenhouse.io/tubitv/jobs/2338145
Post-Doc at University at Albany - SUNY
University at Albany - SUNY
We are looking for a postdoctoral fellow, for an NSF-Funded project, who is interested in developing predictive models to identify and detect procrastination processes in students while studying in an online learning environment and recommendation methods to mitigate procrastination. The postdoctoral fellow will work in the Computer Science Department, as part of an interdisciplinary team with an expertise in machine learning and education, at the State University of New York – Albany, Albany, USA. The research has an emphasis on temporal and social modeling of student data, using point process models and collaborative filtering. Requirements:
PhD (or near completion of PhD) in machine learning, or computer science with a focus of machine learning or recommender systems;
A strong research record, documented by recent publications in the past 3 years;
Good communication skills and fluency in English;
Being highly motivated and creative, enjoying working in a collaborative research environment.
The position is provided for up to 2 years with competitive salary. The starting dates are flexible (available starting Oct 1st, 2020). Applications will be considered until the position is filled. Please send your detailed CV (including the contact information of two references) and a one-page research statement, discussing how your background fits the requirements and topic to Dr. Sherry Sahebi at ssahebi@albany.edu and Dr. Reza Feyzi Behnagh at rfeyzibehnagh@albany.edu with the subject “Postdoc Application”.

Link: http://www.cs.albany.edu/~sherry/opportunities.php
Machine Learning Research Engineer - Cortex Recommender Systems Research
Twitter
At Twitter, we would like to connect people with the conversations, topics and content that are most relevant to them, in real-time. We are a community of Machine Learning Researchers and Engineers, working to drive Twitter’s research in recommender systems. We tackle local and global technical challenges amongst product teams through a range of systems - e.g. timelines ranking, push notifications, email notifications and ads predictions. We operate at scale whilst ensuring fair and ethical use of our models and data.

Requirements:
Experience with large-scale systems and data, e.g. Hadoop, distributed systems
Publications in top conferences such as ICLR, NeurIPS, ICML, RECSYS, CVPR, ICCV, ECCV, etc
Experience with one or more of the following:
Recommender Systems
Model optimisation
Prediction / Inference (e.g. Bayesian)
Deep Learning
Online Learning
Reinforcement Learning
Link: https://careers.twitter.com/en/work-for-twitter/202008/dca8d4c6-b25a-4148-832a-988ea332f93c/6bb6e344-4bec-4cdb-adf9-85be188a9daf.html/machine-learning-research-engineer-cortex-recommender-systems-research.html
RecSys in Norway!
Norway
Join us at the University of Bergen in Norway (world ranking: #194) to establish the brand-new center "MediaFutures"!

The center aims to build the Future of Media technology by researching on trending topics such as Fairness, Diversity, and Transparency in media. We will soon hire PhDs and Postdocs who will work together to create a responsible Media technology.

Interested to join? Follow us:
Web: http://dars.uib.no
Twitter: https://twitter.com/mehdielaahi
LinkedIn: https://linkedin.com/in/mehdielahi
News: https://www.uib.no/en/infomedia/130829/mediafutures-research-centre-responsible-media-technology-innovation
Link: http://dars.uib.no
Senior Information Retrieval Scientist - Tempus
Tempus
The ideal candidate has significant expertise in the Natural Language Processing (Information Retrieval) and biomedical domain, and is eager to apply his or her skills to improve patient outcomes.

What You Will Do:

Design and prototype novel Information Retrieval and Deep Learning Natural Language systems.
End-to-end large scale machine learning model integration.
Collaborate with product, science, engineering, and business development teams to build the most advanced data solutions in precision medicine.
Interrogate analytical results for robustness, validity, and out of sample stability.
Document, summarize, and present your findings to a group of peers and stakeholders.
Link: https://www.tempus.com/careers/job/?gh_jid=4828372002
Machine Learning Scientist - Knowledge Graphs - Tempus
Tempus
The ideal candidate has significant expertise in the Natural Language Processing (Knowledge Graphs) and biomedical domain, and is eager to apply his or her skills to improve patient outcomes.

What You Will Do:

Design and prototype novel Knowledge Graph-based and Deep Learning Natural Language systems.
End-to-end large scale machine learning model integration.
Collaborate with product, science, engineering, and business development teams to build the most advanced data solutions in precision medicine.
Interrogate analytical results for robustness, validity, and out of sample stability.
Document, summarize, and present your findings to a group of peers and stakeholders.
Link: https://www.tempus.com/careers/job/?gh_jid=4828359002
Search & Discovery Product Analyst
Adevinta
Adevinta is a marketplace specialist, operating digital marketplaces in 16 countries in Europe, Latin America and North Africa. Our leading local brands include Leboncoin in France, InfoJobs in Spain, Subito in Italy, Jofogás in Hungary, and Segundamano in Mexico, among many others. Adevinta’s local marketplaces thrive through global connections and networks of knowledge.

We are looking for a product analyst to join us to work in the Search and Discovery area. The goal is to be part of a team to leverage analytics and data driven approach in the areas of Search and Discovery (Recommenders). This person is going to report to the head of analytics in the area of Search & Discovery and work very closely with the product manager of the products.
Link: https://smrtr.io/4qtwD
Search & Discovery Data Engineer
Adevinta
Adevinta is a marketplace specialist, operating digital marketplaces in 16 countries in Europe, Latin America and North Africa. Our leading local brands include Leboncoin in France, InfoJobs in Spain, Subito in Italy, Jofogás in Hungary, and Segundamano in Mexico, among many others. Adevinta’s local marketplaces thrive through global connections and networks of knowledge.

Search Engineering is a new team comprised of highly skilled and senior engineers; experts in the search domain. We are building a global Search Component in our Paris Hub which we will quickly take on a journey from MVP to 100 +million unique users a month as we integrate the product with our marketplaces all over the world.
Link: https://smrtr.io/4qtzt
NLP Researcher
Comcast-Voice Assistant Team
As a lead researcher in the Natural Language Processing (NLP) group, you will be part of a team of researchers and engineers to build the core algorithms powering a voice platform used by millions of people every day. We use advanced Machine Learning (ML) to build a conversational NLP system that understands the user’s intent, whether they are looking for the latest movies or trying to access their bill. You will join our rapidly growing Applied AI research and engineering team that is responsible for the full stack and operationalization of high-profile products and services at Comcast.
Link: https://jobs.comcast.com/jobs/description/tpx-jd-template?external_or_internal=external&job_id=219184
Software Developer – Voice Assistant
Comcast - Voice Assistant
As a software developer, you will work to add new features and improve existing features of the systems that support our content discovery experience. You will collaborate with developers in small, autonomous teams to build systems that are used by millions of people every day.
Sr Machine Learning Research Scientist - Recommendations, Apple Media Products
Apple
Research, design and develop machine learning models for iTunes & App store recommendations. Propose, prototype and evaluate the algorithm improvements.
Build personalized recommender systems for Apple Music, Apps & Games Recommendations, Video, Podcast and Books Recommendations using one or more of the following methods: Deep Learning, Matrix Factorization, Factorization Machines, Text Mining, NLP, Learn to Rank models etc.
Build a pipeline for analyzing big data that consists of both content and user data on Hadoop using map/reduce techniques.
Link: https://jobs.apple.com/en-us/details/200172755/sr-machine-learning-research-scientist-recommendations-apple-media-products?team=SFTWR
Data Scientist
Procter & Gamble
Please visit https://www.pgcareers.com/us-datascience to learn about a range of data science roles in Procter & Gamble.
Link: https://www.pgcareers.com/us-datascience
Data Engineer-Recommender Systems
Comcast - Recommendation Team
We are looking for a mid-level data engineer that would be part of our rapidly growing AI Discovery & Personalization team that owns the full stack and operationalization of our personalized product offerings. You will be responsible for designing and building data pipeline components for the Comcast Personalization/Relevance Platform that is used by millions of customers of Comcast and its partners every day. We use sophisticated Data Pipelines which consume, and process millions of events generate training datasets and populate the events to the highly scalable and performant databases. You will work with other engineers and researchers from our Algorithm team who build and own a variety Machine/Deep Learning models over this data to personalize the content the users watch. As a key member of the team, you will help define, refine, and test state of the art data pipelines, and scale the associated systems for high performance, stability, and availability in the cloud.

Comcast’s Technology, Product & Experience organization encourages career development with regular opportunities for training and programs for innovative cross-team projects such as week-long Hackathon and job rotation programs over the summer.
Link: https://career8.successfactors.com/sfcareer/jobreqcareer?jobId=220307&company=21114P
Research Lead – Personalization
Spotify
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Daily Mix to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.

We are looking for a Research Lead for Spotify’s Personalization organization. Our interdisciplinary team focuses on ensuring that the foundations of Spotify technologies are at or above the state of the art and, in the process, redefine the state of the art for the field. As such, our team has strong ties internally to product groups as well as externally to the research community.

Read the full description at https://spotifyjobs.com/job/research-lead-personalization/
Link: https://spotifyjobs.com/job/research-lead-personalization/
Engineering Manager – Personalization Platform
Spotify
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Daily Mix to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.

We are looking for an Engineering Manager in Boston with expertise in high-scale, machine-learning-driven systems to give management to engineers and leadership to teams in our Personalization Platform product area. The Personalization Platform helps power Spotify’s personalized features whether listening experiences like Your Daily Drive and Daily Mix or means of exploration like Search and Home. It is built by technologists, product insight specialists, designers, and product managers in both Boston and New York, with customers in those offices as well as Stockholm and London.

Read the full description at https://spotifyjobs.com/job/engineering-manager-personalization-platform/
Link: https://spotifyjobs.com/job/engineering-manager-personalization-platform/
Sr. Machine Learning Eng. – Podcast Personalization
Spotify
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Daily Mix to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.

Who You Are
- You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with experience and expertise in personalized machine learning algorithms, especially recommender systems
- You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages. Experience with TensorFlow, PyTorch, Scikit-learn, XGBoost, etc is a strong plus
- You have experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it, Scio and cloud platforms like GCP or AWS
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation
- You love your customers even more than your code

Read the full description at https://spotifyjobs.com/job/sr-machine-learning-eng-podcast-personalization/
Link: https://spotifyjobs.com/job/sr-machine-learning-eng-podcast-personalization/
Data Engineer – Personalization
Spotify
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Daily Mix to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.

Spotify is looking for a Data Engineer to join us. You will build data driven solutions to bring music and digital media experiences to hundreds of millions of active users and millions of creators by matching fans with creators in a personal and relevant way. You will take on complex data-related problems using some of the most diverse datasets available — user behaviors, acoustical analysis, revenue streams, cultural and contextual data, and other signals across our broad range of mobile and connected platforms. Above all, your work will impact the way the world experiences art.

Read the full description at https://spotifyjobs.com/job/data-engineer-personalization/
Link: https://spotifyjobs.com/job/data-engineer-personalization/
Machine Learning Research Scientist – Personalization
Spotify
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Daily Mix to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.

You will be part of an interdisciplinary team focusing on ensuring that the foundations of Spotify technologies are at or above the state of the art and, in the process, redefine the state of the art for the field and contributing to the wider research community by publishing papers. Our team has strong ties internally to product groups as well as externally to the research community.

What you’ll do:
- You will participate in cutting edge research in one of Machine Learning, Language Technologies, Information Retrieval, Human-Computer Interaction, Algorithmic Bias.
- You will work on practical applications such as recommendation, search, voice and language understanding, and areas related to music and podcast streaming.
- You will have product impact, while working on and further developing a long-term research roadmap.
- External engagement such as publishing, giving talks, and being an active community member at top conferences is encouraged.

Read the full description at https://spotifyjobs.com/job/machine-learning-research-scientist-personalization/
Link: https://spotifyjobs.com/job/machine-learning-research-scientist-personalization/
Senior Data Scientist
Analog Devices, Inc.
Join a group of entrepreneurial data scientist and data engineers who are driving hundreds of millions of dollars in revenue growth at Analog Devices. https://careers.analog.com/job/ANLGUS6642/Sr-Data-Scientist
Link: https://careers.analog.com/job/ANLGUS6642/Sr-Data-Scientist
AI Engineer
Bloomberg
Bloomberg offers unparalleled coverage across News and Social Media, Alternative Data, Research, and Live Markets to our clients. In addition, we provide advanced tools to retrieve information, run analyses and execute trades. Bloomberg's Artificial Intelligence (AI) group is the central group of researchers and engineers working to bring relevant, meaningful, tradable, and actionable financial information to our clients using Artificial Intelligence. Some products we build include:

 Real-time analytics over news, social media and structured market data

 Federated search and discovery through question answering and information extraction

 Automation for workflows and content generation

 Dialogue understanding for trades or earning calls

 Security and portfolio pricing

 Models and software for fundamental problems in ML, NLP, and IR

 
All with more strict latency constraints than most academic and industry standards.
We build customer-facing products, as well as AI infrastructure and algorithms used by engineers across the company. We also publish papers, attend conferences, organize workshops, and contribute back to the larger AI and open source community whenever we can. Broadly, we are looking for colleagues to who are passionate about:
 

 Software engineering

 Parallel and distributed systems

 Natural language processing

 Information retrieval

 Information extraction

 Reinforcement learning

 Graphical models

 Recommender systems

 Knowledge graphs

 Parallel and distributed computing

 Automatic speech recognition

 Machine learning for finance (pricing and recommendation)
Link: https://careers.bloomberg.com/job/detail/84512
AI Engineer
Bloomberg
Bloomberg offers unparalleled coverage across News and Social Media, Alternative Data, Research, and Live Markets to our clients. In addition, we provide advanced tools to retrieve information, run analyses and execute trades. Bloomberg's Artificial Intelligence (AI) group is the central group of researchers and engineers working to bring relevant, meaningful, tradable, and actionable financial information to our clients using Artificial Intelligence.

Some products we build include:

 Real-time analytics over news, social media and structured market data

 Federated search and discovery through question answering and information extraction

 Automation for workflows and content generation

 Dialogue understanding for trades or earning calls

 Security and portfolio pricing

 Models and software for fundamental problems in ML, NLP, and IR

All with more strict latency constraints than most academic and industry standards.
We build customer-facing products, as well as AI infrastructure and algorithms used by engineers across the company. We also publish papers (see techatbloomberg.com/ai), attend conferences, organize workshops, and contribute back to the larger AI and open source community whenever we can. Broadly, we are looking for colleagues to who are passionate about:

 Software engineering

 Parallel and distributed systems

 Natural language processing

 Information retrieval

 Information extraction

 Reinforcement learning

 Graphical models

 Recommender systems

 Knowledge graphs

 Parallel and distributed computing

 Automatic speech recognition

 Machine learning for finance (pricing and recommendation)
Link: https://careers.bloomberg.com/job/detail/85011
Senior Machine Learning Engineer
Vinted
Vinted is Europe’s biggest second-hand fashion marketplace. Our mission is green: we want to make second-hand the first choice globally. Recently, Vinted reached a major milestone – we became financially self-sustaining, and we’re still growing fast.

Currently, 30 million people use our platform, which is developed and supported by a team of 450+ people from our offices in Vilnius, Berlin, Prague, and Warsaw. We have a unique work culture that’s based on trust, honesty, and attention to self-improvement.

As part of Vinted’s Product Engineering teams, you’ll be developing new features for our members – all the way from concept to roll-out. We’re upgrading how we use machine learning to make our product better, so you’ll be part of a small, expanding team who focus on building models and applying deep learning to unstructured data.

You’ll be involved in decision-making, have clear task ownership, and participate in regular tech-lead meetups. And – last but not least – you’ll be working with a state-of-the-art tech stack: Python, Jupyter Notebook, TensorFlow with Keras API, PyTorch and Spark.
Link: https://jobs.lever.co/vinted/c63315f5-fa6a-41c5-8247-c15fb201484a
Machine Learning Scientist - Prime Video Recommendation
Amazon
Do you want to know about new movies and TV shows that you'll will enjoy the day they come out? So do millions of our customers, world wide. Did you know we have a wide range of niche content including Natural Park documentaries, Kung-fu movies, or Korean dramas on our service? No? Well, we're looking to change that. Come be part of history, as we fulfill Prime Video's vision of being customer's first place to find something to watch

We're using cutting edge approaches such as graph convolutional networks (GCNs) to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know exitsed. We are looking for creative & customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external ML conferences (e.g. https://dl.acm.org/citation.cfm?id=3292500.3330675).

At the end of the day, you will be innovating and experimenting in a complex technical and business space - dealing with Amazon scale, different types of video assets (Movies, TV Shows, Live Sports, Short Videos) and balancing various business offerings (Prime, Third party channels) - positively impacting millions of customers worldwide.

If you're interested, please send me your resume via LinkedIn:

https://www.linkedin.com/in/aliroshanghias/
Link: https://www.amazon.jobs/en/jobs/1135407/machine-learning-scientist-prime-video-recommendations
Staff Machine Learning Engineer
Twitter
Who We Are
Twitter's Discovery teams are dedicated to getting the majority of the world to converse in public using Twitter. We are composed of many teams across the company, including Product, Engineering, Design, and Research. These teams are responsible for understanding the needs of new users and users who are not very active, and help them discover the value of Twitter by building personalized products.

This mission is to instantly connect people with conversations and audiences most meaningful to them. Realizing this goal involves work in areas such as machine learning, applied data science, recommendation systems, and information retrieval systems. Do you want to make a huge impact while working with large data sets at scale? If so, a Discovery team is a good fit for you!


What You’ll Do
You'll work with an awesome team of engineers, product managers, data scientists, researchers, and designers to build experiences powered by large-scale recommender systems. This includes:

Collaborating with cross-functional partners to come up with roadmaps for Machine Learning driven products for the team.
Working with product engineers to identify product metrics that causally impact business metrics.
Applying data mining, machine learning, and/or graph analysis techniques to a variety of modeling, relevance, and recommendation problems to build production-quality solutions that balance complexity and performance.
Participating in the engineering life-cycle at Twitter, including designing high-quality ML infrastructure and data pipelines, writing production code, conducting code reviews, and working alongside our infrastructure and reliability teams.
Mentoring other engineers on the team and up-level them on applied product ML skills.
Although you will work on groundbreaking problems, this position is not a research position.
Link: https://careers.twitter.com/en/work-for-twitter/202008/db23a25f-c792-49bd-9254-500ba47ebd86/a5a11bcd-da12-499d-8de2-0031b337143a.html/staff-machine-learning-engineer-discovery.html
Machine Learning Engineer
Twitter
Who We Are
Twitter's Discovery teams are dedicated to getting the majority of the world to converse in public using Twitter. We are composed of many teams across the company, including Product, Engineering, Design, and Research. These teams are responsible for understanding the needs of new users and users who are not very active, and help them discover the value of Twitter by building personalized products.

This mission is to instantly connect people with conversations and audiences most meaningful to them. Realizing this goal involves work in areas such as machine learning, applied data science, recommendation systems, and information retrieval systems. Do you want to make a huge impact while working with large data sets at scale? If so, a Discovery team is a good fit for you!


What You’ll Do
You'll work with an awesome team of engineers, product managers, data scientists, researchers, and designers to build experiences powered by large-scale recommender systems. This includes:

Collaborating with cross-functional partners to come up with roadmaps for Machine Learning driven products for the team.
Working with product engineers to identify product metrics that causally impact business metrics.
Applying data mining, machine learning, and/or graph analysis techniques to a variety of modeling, relevance, and recommendation problems to build production-quality solutions that balance complexity and performance.
Participating in the engineering life-cycle at Twitter, including designing high-quality ML infrastructure and data pipelines, writing production code, conducting code reviews, and working alongside our infrastructure and reliability teams.
Mentoring other engineers on the team and up-level them on applied product ML skills.
Although you will work on groundbreaking problems, this position is not a research position.
Link: https://careers.twitter.com/en/work-for-twitter/202009/df334822-33d5-49fd-aa19-856f384228c3/4ad494f2-c1dd-45a6-9981-debf0d8312bf.html/machine-learning-engineer-discovery.html
Senior ML Software Engineer - Ads Targeting
Twitter
Who we are:

Our mission is to leverage state of the art machine learning and data science techniques to allow advertisers effectively reach hundred millions of twitter users who resonate with their business, in a way that protects the integrity of their brand.

This includes applying machine learning techniques to both user modeling and content modeling: examples include inferring user demographics and interests, predicting the probability a user will engage with an ad, and topic modeling for mixed-media containing text, image, and videos! For every ad shown on Twitter, our prediction systems evaluate thousands of ad candidates behind the scene to find the best one. When executed successfully, we create aha! moments for our users & advertisers and add huge value to the Twitter business & revenue.

What You'll Do:

Machine Learning -- apply machine learning and data mining techniques for a variety of modeling and relevance problems involving users, their tweets, their interests, twitter ads, relationship among entities. Be a key contributor to Twitter’s continued use of cutting edge machine learning in all aspects of our solutions. Help guide and mentor this rapidly changing space that helps our users get the right message from their favorite brands and just the right time.
Infrastructure -- Work with our infrastructure teams to contribute to solutions, crack tough problems and mentor engineers on a highly scalable machine learning systems
Products -- Work cross functionally with our product management team to build new solutions for Advertisers, and prove via experimentation that they deliver value to them

Apply your expertise in distributed systems and machine learning to simplify the immense complexity of wrangling with humongous amounts of underlying data, enabling Twitter to deliver more value to our partners.
Link: https://careers.twitter.com/en/work-for-twitter/202008/4707cd26-46c7-44d0-8967-1a5cb4ffc77f/e7b59107-f9f2-4c79-b02a-c96e6e1f2dee.html/senior-ml-software-engineer-ads-targeting.html
Sr Software Engineer - Onboarding Product
Twitter
Who We Are: Twitter’s Onboarding team creates engaging product experiences that help new users fall in love with Twitter. From building recommendation systems to large scale product platforms used by the entire company, there is a little bit of everything on the Onboarding team. Some of the Twitter features you’ll work on: Sign up flow UX and personalization, user education, account recommendations, and much more. This team has a high impact at Twitter, our features are paramount for creating long term user retention on the platform. In this specific role we are looking for a senior engineer who can build great product experience, mentor junior engineers, and be a strong partner across EPDR to execute high impact projects.

Job Description
What You'll Do: As a software engineer at Twitter, you will help us build, scale and maintain the consumer product we have, which has a direct impact on the lives of our users and the success of our business. To be successful you will have to partner closely with Product, Design, Research, Data Science, and other engineers to plan, implement, and validate solutions to user problems.

A few things that set us apart:

Our work is highly impactful, we drive a ton of key metrics for the company (think DAUs, MAUs & various key engagement metrics).
We have some great product platforms that we built over the years to ease the product development
We are very much experiment driven and have several experiments in flight at any point of time
We believe in team-centric development and working in collaboration. We love hanging out together and have many active chat channels, some for work-related topics, and others for non-work related topics
Link: https://jobs.smartrecruiters.com/Twitter2/743999718828074-sr-software-engineer-onboarding-product?trid=33221b55-7baa-4189-992e-a7fac0c08950
Director of Machine Learning - Recommender Systems
Camcast
I'm looking for a someone to lead our team of talented researchers and engineers building Comcast's search and recommender systems.
Link: None
Data Scientist
Walmart Global Tech
The @WalmartLabs Personalization team consists of platform engineers, application engineers, scientists, and product visionaries all working together to design, prototype, and build technology-driven products and experiences for the future landscape of e-commerce.

Prior relevant working experience or research experience required. Particular areas of interest: graph neural networks, unbiased learning, voice personalization.
Link: https://walmart.wd5.myworkdayjobs.com/WalmartExternal/job/US-CA-SUNNYVALE-Home-Office-GEC-Sunnyvale-Bus-Pk-Bldg-D/Data-Scientist--eComm---Personalization_R-297419-2
Applied Scientist - Machine Learning & DL
ZALANDO SE
As an Applied Scientist in the Berlin based Size and Fit Org., you will develop algorithms designed to provide Zalando fashion retail customers with the information they need to make choices that reflect their unique size and fit preferences.

WHERE YOUR EXPERTISE IS NEEDED
* Bring in your experience in developing and deploying Machine Learning and Deep Learning algorithmic based solutions and prototypes to help customers make sense out of confusing sizing systems
* Propose, build and lead initiatives - feature ownership from development to deployment
* Build upon your existing engineering and scientific skills and continue developing them

WHAT WE’RE LOOKING FOR
* Ph.D or M.Sc. with equivalent experience in Machine Learning / Data Science / DL and solid understanding of best practices in feature extraction, dimensionality reduction, model validation, and classification
* Programming languages: Python, and its libraries such as pandas, numpy, scipy
* Hands on experience with ML/DL frameworks such as Tensorflow, Keras, Pytorch, Caffe/Caffe2.0
* Attention to code quality by writing high-performance reusable code

Link: https://jobs.zalando.com/en/jobs/2352248/?gh_jid=2352248
Data Engineer (Machine Learning Engineer)
Flaconi GmbH
We need a skilled DE that would collaborate closely with Data Science Team. Closing the gab between DE and DS.
In particular we are working on scaling our Infra to Ariflow + S3 + Pyspark + Sagemaker on AWS for real time recommendation.
Add me on LinkedIn and I can give you more details, if your interested.

https://flaconi-jobs.personio.de/job/221041?language=en
Link: https://flaconi-jobs.personio.de/job/221041?language=en
Data Ops
Flaconi GmbH
We need a Data Ops (Dev Ops) that support the Data Science and Data Engineering team to scale and optimise out Machine Learning Continuous Integration and Delivery pipeline.
Stack: K8S, Python, AWS, Sagemaker, Travis, Terraform.
Stack to be: Pyspark, Airflow.
Contact me on LinkedIn for more details
Link: https://flaconi-jobs.personio.de/job/186190?language=en
Data scientist в Лабораторию искусственного интеллекта Сбербанка
Sberbank
Рекомендательная группы Лаборатории искусственного интеллекта Сбербанка ведет широкомасштабный поиск исследователей и data scientists. У нас есть несколько позиций разного уровня, от junior до senior.

Лаборатория занимается вопросами применения искусственного интеллекта в области медицины, финансов, экономики, бизнеса и проч. Мы ведем работу как в научно-практической, так и в теоретической плоскостях. У нас есть широкий спектр проектов в области рекомендательных систем, от научных до практических.

Задачи:

Глубокое погружение в предметную область,
Анализ научной литературы,
Подготовка и анализ данных,
Генерация и проверка гипотез,
Разработка моделей и программного кода.
Требования:

Знание основных алгоритмов и структур данных
Знание базовых вещей в теории вероятностей, математическом анализе, линейной алгебре
Умение программировать на любом mainstream языке (Python или C++)
Понимание основ recommender systems или желание изучить их
Умение анализировать научную литературу, разбираться в незнакомой теме
Опыт создания и внедрения рекомендательных систем будет огромным плюсом
От нас:

Конкурентоспособная зарплата
Дружный и высококвалифицированный коллектив
Тренажерный зал в офисе
Гибкий график
Оплата посещения конференций (ICML, NeurIPS, ICDM, MICCAI etc.), научная литература и проч.
Для этой вакансии умение программировать является абсолютным обязательным требованием.

Расположение: Москва, Оружейный пер., д. 41

Мы готовы предложить следующую компенсацию:
Junior ~ 100-150 тыс. руб. (gross),
Middle ~ 150-200 тыс. руб. (gross),
Senior ~ 200-300 тыс. руб. (gross),
а также премии сопоставимые с годовым доходом.

Рамки могут быть расширены для людей с большим опытом и знаниями в рекомендательных системах.

Резюме просьба высылать на адрес Isakhanyan.I.G@sberbank.ru с темой “Лаборатория ИИ, Рекомендательные системы”.
Senior Software Development Engineer- Search
Capital Group
Responsibilities
You will independently implement new features in a highly collaborative work environment alongside product managers and fellow engineers.
You will write legible, resource-efficient, and performant code.
You will collaborate with business partners and internal customers.
You will share technical solutions and product ideas through team planning, design review, pair programming, code review, and technical discussions.
You will take on projects and make software enhancements that improve team software and processes.
While you are an agent of change with a sense of urgency, you are respectful of what came before.
Link: https://jobs.capitalgroup.com/job/Los-Angeles-Software-Development-Engineer-Senior-IG-Tech-Search-CA-90071/650898500/?feedId=217600&utm_source=LinkedInJobPostings&utm_campaign=CapitalGroup_LinkedinSlots
Product Owner - Recommendation System
leboncoin
Hi,

We are looking for a Product Owner for the Recommendation System team.
You will be working at the French leader in classified ads. We are one of the Top10 most visited website in France and have 33M classified ads in the catalog.

Feel free to contact me
Link: https://www.smartrecruiters.com/Adevinta/743999720374530-product-owner-confirme-e-machine-learning-
Engineering Manager - Data Insight Platform
leboncoin
Hi,

We are looking for an Engineering Manager for the Data Insight Platform.
You will be working at the French leader in classified ads. We are one of the Top10 most visited website in France and have 33M ads in the catalog.

Feel free to contact me
Link: https://bit.ly/33rFTBt
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